Abstract Details


Poster 35: An Extended Analysis on Turbo Similarity Searching

Alia-Azleen Zainal1, Norasyikin Yusri1, Yong Pei Chia1, Nurul Malim1, Shereena M Arif2
1School of Computer Sciences, Universiti Sains Malaysia
2Information School, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia
Drug discovery is a vital part in chemoinformatics where various techniques are being incorporated in order to discover novel chemical entities (NCE’s). Similarity searching (SS) is important in the field of chemoinformatics and has helped a lot in making the process of drug discovery a lot simpler plus to be conducted in shorter period time. Turbo similarity searching (TSS) has then come along with group fusion which is based on the nearest neighbors (NN) concepts and the use multiple reference compounds which has been proven to increase the performance of SS. In this research we would like to investigate the effect of using different combinations of similarity measures on TSS, to determine the effect of fusion rules towards the performance of TSS and to implement a new strategy in hopes to find a better way to conduct TSS so that better results can be obtained and at the same time improve the process of drug discovery.

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